Diffusion Models and Consumer Behavior: Adopting & Disseminating Technology & Innovations - Essay Sample

Introduction

The adoption and dissemination of technology and innovations is a relevant topic in the literature on consumer behavior. Within research on this topic, two types of models are distinguished. A first type is the models that try to increase the understanding of the diffusion process as a whole. These models are analytical representations of a dissemination process at the aggregate level. They are often referred to as diffusion models.

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The second class of model aims to provide clarity regarding the factors that determine the decision of adoption (or non-adoption) of the individual. These models take a disaggregated perspective and are generally known as adoption models (Venkatesh & Davis, 2000). Consequently, it can be said that the adoption of technology is the process by which a consumer begins to buy and use new technology.

On the other hand, the diffusion of technology describes how the use of it extends through a specific population. All innovation adoption models have three underlying phases: cognitive, affective (evaluative) and behavioral (conative) (Venkatesh, 2000). In the cognitive phase, the consumer considers mentally or is exposed to the product, service or idea. Thus, the consumer develops a set of opinions or beliefs about the characteristics of the product.

These ideas are used to form feelings towards the product (affective phase). Based on the feelings, the consumer undertakes the actions in the behavior phase. In the study of adoption processes related to technology, two types of models have been applied: normative models and expected value models. Each of these models is based on one of the traditions of the literature of cognitive psychology and social psychology, respectively.

Performance Expectancy

Performance expectancy can be described as the degree to which a person believes that by using a certain technology, he/she will achieve performance gains in his/her attributions and enhance job performance (Venkatesh et al., 2003). It was founded in the constructs of different models: Utility perceived coming from the models of TAM (Technology Acceptance Model) and TAM-TPB, extrinsic motivation originating from the MM model, setting the work from the MPCU model, relative advantage from the RTD model and expectancy results from the SCT model.

The adoption of new technologies cannot be understood without the conviction of the person who incorporates them that they benefit from their use, and this can occur at work or in personal life. If a person does not believe that the incorporation of these elements will be useful, it will be more difficult to acquire them (Sung, Jeong, Jeong, & Shin, 2015). This issue is important because it is no longer a matter of positive or negative predisposition, but whether people have a mobile or tablet as a short-term investment. Therefore, if predisposition is a fundamentally passive issue, the intention is proactive and implies the desire to have this technology in daily life.

One such example is the use of LinkedIn among professionals. Individuals are aware that by using LinkedIn, they can gain professional benefits such as: acquiring more contacts, looking for new career opportunities or obtaining information related to the corporate environment and its areas of activity (Benbasat & Barki, 2007). This is because LinkedIn has a variety of services with professional focus in which they make it possible to display professional information with the interaction between stakeholders.

Since LinkedIn Professional Social Networking enables one to quickly share professional information, improve the chances of benefits with one's contacts, increase the chances of getting opportunities and other possibilities, it is assumed that the perception of these benefits can influence the intention to use the social network (Alraja, 2015). Some individuals with the intention of turnover possibly seek tools, media, new technologies such as the LinkedIn professional social network, seeking to disseminate their professional information, locate professional opportunities, obtain information about the job market, get more contacts, among other reasons.

One of the most influential approaches to model the adoption of technological products is the so-called normative model, where the consumer selects the alternative that provides the greatest objective utility (performance expectancy), is usually determined by a compensatory procedure between the expectations of profit and the costs that may be incurred. The central elements of the normative models are rationality and optimization.

A physical stimulus, such as the attributes of a product, supposes a first influence on the perceptions that, later, determine an affection or preference for the products, leading to the choice. The Expected Values model is also known as Multi-Attribute, Linear Compensatory or Fishbein Attitude models. The expected value models have a long tradition in marketing research (Aarts & Gorman, 2007). The underlying hypothesis is that an attitude towards an object (or action) is a function of one's beliefs about the attributes of the object (or consequences of the action) and its evaluation of the affective reactions towards the individual attributes (or consequences).

The adoption of information technology or communication systems, in many organizations, is imposed by management and, therefore, is not a volitional act in which an election occurs. The voluntary variable would change the relative importance of the perceived characteristics of innovation. Intrinsic motivation leads to behaviors for pure personal pleasure and not for an external reward.

No external reinforcement is necessary to the individual and the behavior is performed simply by its inherent diversion. Many behaviors are made for this reason and the authors of the TAM argue that the use of a computer system in the workplace is one of them. They argue that users value the use of computer science for personal reasons rather than for organizational efficiency and the rewards they imply for the worker (Gatewood, Shaver, Powers, & Gartner, 2002). The perception of how easy a system is to use and its quality also have a positive effect on entertainment, since they represent two different information resources relevant to feelings of self-efficacy, competence, and self-determination, which are elements of intrinsic motivation.

Effort Expectancy

The expectations of effort are defined as the user's perception of the ease in the use of technology. It was founded in the constructs of different models: Perceived Ease of TAM, TAM2, Complexity Model MPCU and ease of use of the RTD. There are similarities in the definitions of the constructs and in their measurement scales (Venkatesh et al, 2003, p. 450). They are directly related to factors such as experience or familiarity and may be due to the inclusion of other variables such as hedonic motivations or habit.

These are factors that have a positive influence on the use of technology and people find it easy to use. The level of development of technology in a country is inversely related to the significance of the variable expectations of effort on technology (Ghalandari, 2012). It is found that, in the countries where its development is initial, this variable is not significant and that the opposite occurs in developed countries, the influence of the effort expectations in technology being high.

The expectations of effort and the facilitating conditions will tend to have high levels of influence on the intention of using technology when its diffusion in a country is at levels of massification or high diffusion in society. Effort expectancy is directly related to perceived ease of use. Ease of use refers to the work that is going to be done because of the adoption of new technologies and, in this case, it must be said that some factors such as expertise will also be fundamental (Oh, Lehto, & Park, 2009). There are people who have had a hard time joining the digital path and taking on small operations such as internet browsing, for example. In many cases, then, the difficulty that a person perceives for the use of new technology can be decisive in deciding, or not, its final adoption. Many technologies that were objectively useful took time to incorporate because their potential users did not perceive them that way.

It is essential, to adopt the new technologies, to know what the population's predisposition towards them is. A person predisposed to use a mobile data connection or WhatsApp messaging will learn to use it faster than a person who is not (Trybou, 2017). The attitude, of course, is a passive question because a worker sees how new technology is incorporated into his job, but it is not he who decides to include it.

The example of LinkedIn can also be used in this case as well. The Expectation of Effort appears as another positive influence on the intended use of the LinkedIn social network. Some individuals perceive aspects related to the ease of use of this system, such as clear and easy to understand interaction, that learning to use it is easy, that it is easy to become an expert in use, among other aspects. Thus, the LinkedIn interface is likely to have features that make handling simple and practical, which may be related to the design changes the platform has undergone and apparently made its interface simpler to use.

It consists in the expectation that by investing "X" effort, "X" results will be obtained. The expectation has a lot to do with the concept of self-efficacy. This concept refers to a person's perceived ability to cope with obstacles and achieve what is proposed. Within the theory of the expectation of Vroom, and referring to the second essential element that leads to motivation, there is instrumentality (Venkatesh, Thong, & Xu, 2012). This has to do with the fact that each worker will have his function and will be an indispensable part so that all the gear works, the organization itself as a whole. The objective will be that the employee has a good performance, which allows obtaining the desired results; that is to say, it has to be a "functional" piece, which brings value.

Another component of the Vroom expectation theory formula is valence, and it has to do with what each employee values; there will be some who value technology more and are more inclined to see it. The role of the employer, in this case, will be to discover what their workers value regarding technology, in addition to knowing what value they give to their own results. In conclusion, the adoption of these technologies depends on the automation of other factors such as the cost of developing and implementing automation solutions for specific uses in the workplace, the dynamics of the markets, the benefits of automation beyond substitution, regulatory issues and social acceptance.

Social Influence

Regarding the external variables (sociodemographic) that affect the individual use of the technology, Venkatesh et al. (2003) established that the education and economic income of each subject explained the use of said technology. The educational level of a subject also impacts users' perception of the usefulness of technology and its use. As the educational level of an individual increase, he/she will probably perform more elaborate tasks, which could encourage him/her to make greater use of technology and demonstrate its usefulness in his/her work. On the other hand, a person with better education will possess skills and knowledge, such as reading, writing, and mathematical skills, which will facilitate the use of technology.

The higher the educational level of a person, the greater their perceived ease of use of technology. The higher the educational le...